Adaptive segmentation-based feature extraction and S-STDM watermarking method for color image

Mianjie Li, Xiaochen Yuan

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

A local color image watermarking scheme using adaptive segmentation-based feature extraction (ASFE) and singular value decomposition-based spread transform dither modulation (S-STDM) is proposed in this paper. The proposed ASFE can adaptively extract feature regions from blocks segmented by the simple linear iterative clustering. In addition, the stationary wavelet transform is employed to decompose each of the extracted feature regions because of its shift invariance. Consequently, the novel S-STDM watermarking method is proposed, where we employ singular value decomposition to calculate the approximation coefficients and then select the generated diagonal elements from the decomposed diagonal matrix for watermark message embedding. The experimental results show that the proposed scheme is superior to the existing schemes under various attacks.

Original languageEnglish
Pages (from-to)9181-9200
Number of pages20
JournalNeural Computing and Applications
Volume32
Issue number13
DOIs
Publication statusPublished - 1 Jul 2020
Externally publishedYes

Keywords

  • Adaptive segmentation-based feature extraction
  • Image watermarking
  • Simple linear iterative clustering
  • Stationary wavelet transform

Fingerprint

Dive into the research topics of 'Adaptive segmentation-based feature extraction and S-STDM watermarking method for color image'. Together they form a unique fingerprint.

Cite this