Feature extraction and local Zernike moments based geometric invariant watermarking

Xiao Chen Yuan, Chi Man Pun

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


A robust and geometric invariant digital image watermarking scheme based on robust feature detector and local Zernike transform is proposed in this paper. The robust feature extraction method is proposed based on the Scale Invariant Feature Transform (SIFT) algorithm, to extract circular regions/patches for watermarking use. Then a local Zernike moments-based watermarking scheme is raised, where the watermarked regions/patches can be obtained directly by inverse Zernike Transform. Each extracted circular patch is decomposed into a collection of binary patches and Zernike transform is applied to the appointed binary patches. Magnitudes of the local Zernike moments are calculated and modified to embed the watermarks. Experimental results show that the proposed watermarking scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation; and common signal processing such as JPEG compression, median filtering, and low-pass Gaussian filtering.

Original languageEnglish
Pages (from-to)777-799
Number of pages23
JournalMultimedia Tools and Applications
Issue number1
Publication statusPublished - Sept 2014
Externally publishedYes


  • Feature extraction
  • Geometric invariant
  • Inverse Zernike transform
  • Local Zernike transform
  • SIFT


Dive into the research topics of 'Feature extraction and local Zernike moments based geometric invariant watermarking'. Together they form a unique fingerprint.

Cite this