Image segmentation-based robust feature extraction for color image watermarking

Mianjie Li, Zeyu Deng, Xiaochen Yuan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Original languageEnglish
Title of host publicationNinth International Conference on Graphic and Image Processing, ICGIP 2017
EditorsHui Yu, Junyu Dong
PublisherSPIE
ISBN (Electronic)9781510617414
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event9th International Conference on Graphic and Image Processing, ICGIP 2017 - Qingdao, China
Duration: 14 Oct 201716 Oct 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10615
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference9th International Conference on Graphic and Image Processing, ICGIP 2017
Country/TerritoryChina
CityQingdao
Period14/10/1716/10/17

Keywords

  • Distortion-Compensated Dither Modulation (DC-DM)
  • Image Segmentation-based Robust Feature Extraction (ISRFE)
  • Robust feature extraction
  • Simple Linear Iterative Clustering (SLIC)

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