A Novel Local Binary Pattern Based Blind Feature Image Steganography
Soumendu Chakraborty, and Anand Singh Jalal

TL;DR
This paper introduces a new blind image steganography method that embeds secret data while preserving local binary pattern features of the cover image, achieving a balance between embedding capacity and visual quality.
Contribution
It proposes a novel feature-based steganography technique that maintains LBP features, enhancing robustness and capacity compared to existing methods.
Findings
Preserves local binary pattern features in stego images
Achieves comparable embedding rates with minimal visual distortion
Outperforms LSB-based methods in robustness and effectiveness
Abstract
Steganography methods in general terms tend to embed more and more secret bits in the cover images. Most of these methods are designed to embed secret information in such a way that the change in the visual quality of the resulting stego image is not detectable. There exists some methods which preserve the global structure of the cover after embedding. However, the embedding capacity of these methods is very less. In this paper a novel feature based blind image steganography technique is proposed, which preserves the LBP (Local binary pattern) feature of the cover with comparable embedding rates. Local binary pattern is a well known image descriptor used for image representation. The proposed scheme computes the local binary pattern to hide the bits of the secret image in such a way that the local relationship that exists in the cover are preserved in the resulting stego image. The…
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