Capacity improved robust lossless image watermarking

Abstract

Nowadays, the lossless watermarking methods that can resist attacks have attracted more attention. Obtaining a robust lossless watermarking was at the cost of reducing the capacity and the watermarked image quality. This study presents a new robust lossless watermarking scheme in the transform domain where the Slantlet transform (SLT) has been applied to transform the host image and blocks of the SLT coefficients have been selected for the embedding process. The histograms of the selected blocks are modified according to a predefined threshold value to carry the watermark bits. The overflow/ underflow of the pixel values have been avoided by using a pixel adjustment method as a post-processing step. In the proposed scheme, the original host image can be recovered without any distortion after the hidden watermark has been extracted and the watermark can withstand different kinds of attacks. In comparison with the previous methods, the proposed scheme has higher embedding capacity, better robustness against unintentional attacks and improved visual quality. The results of the experiments prove the efficiency of the proposed scheme.

Multi-Biometric Watermarking Scheme Based on Interactive Segmentation Process

“…The final subsection presents a general comparison between the proposed MBW and the state-ofthe-art iris image watermarking methods. The SLT-based watermarking methods proved their efficiency in terms of robustness as explained in [27][28], therefore, the robustness test is not repeated in this research paper.…”

“…In recent years, different Slantlet transform (SLT) based watermarking schemes have been presented which proved their efficiency in terms of high embedding capacity, robustness against attacks, and high visual quality [27][28], therefore, a SLT-based watermarking algorithm is applied in the proposed MBW scheme. The procedures of the watermark embedding and extraction in an image block are explained in the following subsections.…”

Handwritten numeral recognition using non‐redundant Stockwell transform and bio‐inspired optimal zoning

“…Exploring and subsequently exploiting the ability to decompose an image into an orthogonal space-frequency representation by the ST, it was intuitive to venture into other possibilities of transformed domain feature extraction approaches. The Slantlet transform, proposed by Selesnick in 1999 [42] has been proved to give good outcomes in 1D data compression in power quality events [43], in image watermarking [44], brain image classification [45], multispectral image fusion [46] and so on, and many times surpassing the performance of wavelets. Therefore we were motivated to take advantage of the Slantlet transform for extracting features for handwritten numeral recognition.…”

Robust watermarking scheme for tamper detection and authentication exploiting CA

“…The fundamental challenges [10] in watermarking are to resist attacks based on modification, compression, scaling, filtering, cropping, copy and paste, collage etc. So efficient watermarking scheme [11] should make a good trade‐off between security, robustness and imperceptibility. Although high embedding capacity is not the main purpose of the watermarking schemes but many of the current researchers [1, 12, 13] are also taken this as one of the important characteristics while possessing the quality of the watermarked image (WI).…”