Robust Digital Watermarking Method Based on Adaptive Feature Area Extraction and Local Histogram Shifting

TL;DR

This paper introduces a robust local digital watermarking technique using adaptive feature area extraction and histogram shifting, which enhances security, capacity, and resistance to various signal processing and geometric attacks.

Contribution

It presents a novel local watermarking method combining feature detection, stationary wavelet transform, and histogram shifting for improved robustness and security.

Findings

Higher image quality after attacks

Lower bit error rate in decoding

Superior performance compared to existing methods

Abstract

A new local watermarking method based on histogram shifting has been proposed in this paper to deal with various signal processing attacks (e.g. median filtering, JPEG compression and Gaussian noise addition) and geometric attacks (e.g. rotation, scaling and cropping). A feature detector is used to select local areas for embedding. Then stationary wavelet transform (SWT) is applied on each local area for denoising by setting the corresponding diagonal coefficients to zero. With the implementation of histogram shifting, the watermark is embedded into denoised local areas. Meanwhile, a secret key is used in the embedding process which ensures the security that the watermark cannot be easily hacked. After the embedding process, the SWT diagonal coefficients are used to reconstruct the watermarked image. With the proposed watermarking method, we can achieve higher image quality and less bit error rate (BER) in the decoding process even after some attacks. Compared with global watermarking methods, the proposed watermarking scheme based on local histogram shifting has the advantages of higher security and larger capacity. The experimental results show the better image quality as well as lower BER compared with the state-of-art watermarking methods.